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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Setup and Administration | 13% | - Data streams, data spaces, and governance - Monitoring, reporting, and tools (Data Explorer, APIs) - Permissions, settings, and security configuration |
| Topic 2: Act on Data / Activation | 18% | - Troubleshooting activation issues and dependencies - Data actions and integration with Salesforce products - Activation types and use cases |
| Topic 3: Data Ingestion and Modeling | 20% | - Ingestion methods, connectors, and transformation - Data mapping, validation, and quality best practices - Customer 360 data model and schema design |
| Topic 4: Segmentation and Insights | 18% | - Segment creation, configuration, and maintenance - AI-powered insights and analysis - Calculated vs streaming insights |
| Topic 5: Identity Resolution and Harmonization | 14% | - Identity graphs and data unification - Matching rules (deterministic / probabilistic) - Reconciliation and result analysis |
| Topic 6: Solution Positioning / Overview | 14% | - Role in AI and predictive capabilities - Common use cases and data ethics principles - Data 360 / Data Cloud terminology and business value |
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NEW QUESTION # 114
A Data 360 Consultant creates a segment of customers who placed orders in the last 30 days and includes related attributes from the Sales Order data model object (DMO) in the activation. After activating the segment to Marketing Cloud, the customer notices that some orders older than 30 days are included. What should the consultant do to resolve this issue?
Answer: D
Explanation:
The segmentation and activation design starts with grain: who or what the audience represents, and which attributes must travel with it. Apply a 30-day date filter on the Sales Order DMO within the activation. works because Data 360 segmentation and activation must respect audience grain, relationship paths, and activation payload rules. A segment can qualify the audience, but activation determines which related attributes or contact points are actually sent downstream. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
NEW QUESTION # 115
A Data 360 Consultant wants to ensure that every segment managed by multiple brand teams adheres to the same set of exclusion criteria that are updated on a monthly basis. What is the most efficient option to allow for this capability?
Answer: C
Explanation:
The segmentation and activation design starts with grain: who or what the audience represents, and which attributes must travel with it. Create a reusable container block with common criteria. works because Data 360 segmentation and activation must respect audience grain, relationship paths, and activation payload rules. A segment can qualify the audience, but activation determines which related attributes or contact points are actually sent downstream. The distractors fall short because they either move the problem into the wrong system, add needless duplication, ignore Data 360 object relationships, or rely on a feature built for a different lifecycle stage. In a real implementation, those choices usually create brittle pipelines, stale data, security exposure, or segments that look correct on paper but fail when activated. Thinking like an architect, the selected option places the logic where Data 360 can govern it and reuse it reliably. This is the nuance exam questions often test: the platform capability must match both the technical layer and the business timing requirement, not just sound related to data.
NEW QUESTION # 116
Which permission setting should a consultant check if the custom Salesforce CRM object is not available in New Data Stream configuration?
Answer: B
Explanation:
To create a new data stream from a custom Salesforce CRM object, the consultant needs to confirm that the View All object permission is enabled in the source Salesforce CRM org. This permission allows the user to view all records associated with the object, regardless of sharing settings1. Without this permission, the custom object will not be available in the New Data Stream configuration2. References:
* Manage Access with Data Cloud Permission Sets
* Object Permissions
NEW QUESTION # 117
A company stores customer data in Marketing Cloud and uses the Marketing Cloud Connector to ingest data into Data Cloud.
Where does a request for data deletion or right to be forgotten get submitted?
Answer: C
Explanation:
Data Deletion Requests: For companies using Salesforce Marketing Cloud and Data Cloud, managing data privacy and deletion requests is essential.
Marketing Cloud Connector: This connector facilitates data integration between Marketing Cloud and Data Cloud, but data deletion requests must follow specific procedures.
Deletion Requests in Marketing Cloud:
* Data Management: Requests for data deletion or the right to be forgotten are submitted through Marketing Cloud settings, where the customer data is originally stored and managed.
* Propagation: Once the request is processed in Marketing Cloud, the changes are propagated to Data Cloud through the connector.
References:
* Salesforce Marketing Cloud Documentation: Data Management
* Salesforce Data Cloud Connector Guide
NEW QUESTION # 118
What does the Ignore Empty Value option do in identity resolution?
Answer: D
Explanation:
The Ignore Empty Value option in identity resolution allows customers to ignore empty fields when running reconciliation rules. Reconciliation rules are used to determine the final value of an attribute for a unified individual profile, based on the values from different sources. The Ignore Empty Value option can be set to true or false for each attribute in a reconciliation rule. If set to true, the reconciliation rule will skip any source that has an empty value for that attribute and move on to the next source in the priority order. If set to false, the reconciliation rule will consider any source that has an empty value for that attribute as a valid source and use it to populate the attribute value for the unified individual profile.
The other options are not correct descriptions of what the Ignore Empty Value option does in identity resolution. The Ignore Empty Value option does not affect the custom match rules or the standard match rules, which are used to identify and link individuals across different sources based on their attributes. The Ignore Empty Value option also does not ignore individual object records with empty fields when running identity resolution rules, as identity resolution rules operate on the attribute level, not the record level.
Reference:
Data Cloud Identity Resolution Reconciliation Rule Input
Configure Identity Resolution Rulesets
Data and Identity in Data Cloud
NEW QUESTION # 119
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